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LFW Funneled Dataset

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Visualization of the LFW Funneled Dataset in the Deep Lake UI.

LFW Funneled Dataset

What is LFW Funneled Dataset?

LFW Funneled Dataset is a face photo database developed to explore the problem of unlimited face recognition. LFW Funneled Dataset has the same images present in the original Labeled Faces in the Wild dataset, however, the images in this dataset are aligned using commercial face alignment software.

Downloading LFW Funneled Dataset in Python

Instead of downloading the LFW Funneled Dataset in Python, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code..

Load LFW Funneled Dataset in Python 

				
					import deeplake
ds = deeplake.load('hub://activeloop/lfw-funneled')

LFW Funneled Dataset Structure

LFW Funneled Data Fields
  • images: tensor containing images of the people
  • names: tensor containing the names of the people depicted in the images

How to use LFW Funneled Dataset with PyTorch and TensorFlow in Python

Train a model on LFW Funneled Dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers = 0, batch_size= 4, shuffle = False)
Train a model on LFW Funneled Dataset with TensorFlow in Python 
				
					dataloader = ds.tensorflow()

LFW Funneled Dataset Creation

Dataset Collection and Normalization Information
In this database, there are over 13,000 face images collected from the Internet. Each face was signed with the name of the person depicted in the image. 1680 of the people pictured have two or more different photos in the dataset. A new method for aligning the images is used in the LFW Funneled Dataset, using poorly aligned examples of unlabeled classes

Additional Information about LFW Funneled Dataset

LFW Funneled Dataset Description

LFW Funneled Dataset Curators
Gary B. Huang, Vidit Jain, and Erik Learned-Miller
LFW Funneled Dataset Licensing Information
Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license. If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!
LFW Funneled Dataset Citation Information 
				
					@InProceedings{Huang2007a, 
author = {Gary B. Huang and Vidit Jain and Erik Learned-Miller},
title = {Unsupervised Joint Alignment of Complex Images},
booktitle = {ICCV},
year = {2007} 
}
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